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nyra health is seeking an Applied Researcher in Audio to develop machine learning models that preserve and understand rich acoustic information for neurorehabilitation applications. Unlike conventional speech systems that simplify audio to transcripts, this role focuses on models that capture timing, prosody, speaker identity, pronunciation, and acoustic context—details critical for clinical care.
You will work across the full research-to-production pipeline: exploring novel architectures for speech understanding, generation, alignment, and representation learning; curating training data and developing synthetic data pipelines; establishing rigorous evaluation benchmarks; and scaling models on modern GPU infrastructure. The role bridges scientific exploration with practical implementation, moving successful prototypes into open releases and production systems used by clinics and therapists.
nyra labs is the research arm of nyra health, which builds software for neurorehabilitation clinics. The team publishes models, datasets, and benchmarks openly while maintaining a direct path from research to real-world clinical impact.
You should have strong background in speech, audio understanding, audio generation, or representation learning, with hands-on PyTorch and large-scale training experience. An MSc, PhD, or equivalent practical experience in machine learning or audio processing is expected. Beyond technical skills, you balance scientific novelty with measurable impact, design rigorous experiments, write clean maintainable Python, and are comfortable working across architecture, data, evaluation, and infrastructure. You are pragmatic about when simple baselines outperform complex models, self-directed in identifying the next useful experiment, and collaborative across researchers, engineers, therapists, and product teams.
The role offers access to clinically grounded speech data, freedom to work across the audio research stack, opportunities to publish openly, and close collaboration with a small ambitious team. nyra health provides attractive compensation, phantom stock options, and company benefits. The position is hybrid based in Vienna's First District.
